An adaptive middleware design to support the dynamic interpretation of domain-specific models |
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| Affiliation: | 1. Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA;2. School of Computer Science, Engineering, and Physics, University of Michigan-Flint, Flint, MI 48502, USA;3. Instituto de Informática, Universidade Federal de Goiás, CEP 74690-815, Goiânia, GO, Brazil;4. School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA;1. Brasília University – UnB, Campus Gama, DF, Brazil;2. National Institute for Space Reserach-INPE, S J dos Campos, SP, Brazil;1. Database Laboratory, Universidade da Coruña, Facultade de Informática, Campus de Elviña s/n, 15071 A Coruña, Spain;2. Yahoo Labs, Barcelona & DTIC, Universitat Pompeu Fabra, Barcelona, Spain;3. DAMA-UPC, Universitat Politèecnica de Catalunya, Campus Diagonal Nord, Building C6, C. Jordi Girona, 1-3, 08034 Barcelona, Spain;1. IIIS Centre for Enterprise Architecture Research and Management, Griffith University, 170 Kessels Rd, Nathan, Brisbane 4111, Australia;2. Tecnológico de Monterrey, Calle del Puente 222, Col. Ejidos de Huipulco, 14380 Tlalpan, México, D.F., Mexico |
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| Abstract: | ContextAs the use of Domain-Specific Modeling Languages (DSMLs) continues to gain popularity, we have developed new ways to execute DSML models. The most popular approach is to execute code resulting from a model-to-code transformation. An alternative approach is to directly execute these models using a semantic-rich execution engine – Domain-Specific Virtual Machine (DSVM). The DSVM includes a middleware layer responsible for the delivery of services in a given domain.ObjectiveWe will investigate an approach that performs the dynamic combination of constructs in the middleware layer of DSVMs to support the delivery of domain-specific services. This middleware should provide: (a) a model of execution (MoE) that dynamically integrates decoupled domain-specific knowledge (DSK) for service delivery, (b) runtime adaptability based on context and available resources, and (c) the same level of operational assurance as any DSVM middleware.MethodOur approach will involve (1) defining a framework that supports the dynamic combination of MoE and DSK and (2) demonstrating the applicability of our framework in the DSVM middleware for user-centric communication. We will measure the overhead of our approach and provide a cost-benefit analysis factoring in its runtime adaptability using appropriate experimentation.ResultsOur experiments show that combining the DSK and MoE for a DSVM middleware allow us to realize efficient specialization while maintaining the required operability. We also show that the overhead introduced by adaptation is not necessarily deleterious to overall performance in a domain as it may result in more efficient operation selection.ConclusionThe approach defined for the DSVM middleware allows for greater flexibility in service delivery while reducing the complexity of application development for the user. These benefits are achieved at the expense of increased execution times, however this increase may be negligible depending on the domain. |
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| Keywords: | Models at runtime Adaptable middleware Domain independence Domain specific classifier |
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